Main Responsibilities:

• Develop high-frequency market-making strategies to ensure their stability and profitability in low-latency and high-frequency environments.
• Utilize statistical modeling, machine learning, and time-series analysis to study market microstructure, build high-frequency trading signal models, and develop high-frequency predictive capabilities.
• Conduct performance attribution analysis of high-frequency strategies to identify sources of returns and risk factors.

Qualifications:

• At least 1 year of verifiable track record with a Sharpe Ratio > 2.
• 2+ years of experience in WEB3 quantitative research and 5+ years in traditional quantitative research.
• Master’s degree or above from a well-known domestic or international university, preferably in Mathematics, Physics, Statistics, Financial Engineering, or related fields.
• Familiarity with the development process and methodology of quantitative strategies, with experience in renowned quantitative institutions being a plus.
• Proficiency in using Python, C++, Java, and other tools to process large volumes of financial data.
• Strong sense of teamwork and communication skills, as well as a high level of responsibility and stress tolerance.

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